Installation and setup: prepare in advance

Before the first workshop, please make sure that you have access to R and RStudio on your laptop. If you need help with the installation, please follow this tutorial.

In addition the R basics tutorial on the Data Center website explains the RStudio interface, and shows how to create a new project and how to install packages.

As a first step, please create a new project in your preferred working directory for these workshops, install the tidyverse package, and load it in your R session at the top of a new script. Note that packages need to be installed only once, but need to be loaded at the beginning of each new R session.

# install.packages("tidyverse")
library(tidyverse)

Objectives

Why R?

Free and open-source
Reproducible
Widely used in academia and industry; up-to-date with the latest technological developments
Very versatile: extensive package ecosystem for statistics and more
Powerful data wrangling and visualization capabilities
Extensive community support (open-access books, tutorials, forums, AI tools, etc.)

Why `tidyverse`?

Clean, consistent, intuitive, readable syntax for all steps of the data analysis process
Limited set of functions that can be combined in many ways
Many packages beyond core tidyverse with the same underlying design, grammar, and data structures, therefore easier to learn advanced techniques

Please use the links in the headers to access the individual sections.

Introduction to R

Data analysis workflow

Finding and importing data

Data wrangling with `dplyr`

Exploratory analysis

Summary statistics

Data visualization with `ggplot2`

Hypothesis testing / modelling

Other resources

Data Center collection of resources

Note: a major advantage of using R is the ability to define custom functions. So if some of the methods and workflows used in RMET classes do not have sufficiently straightforward R implementations, UCR can develop its own functions (and even package) to streamline the process and give students quick and easy functions. See for example the qacr package developed for a similar purpose at Wesleyan University: qacr website.